Connect machine learning with numerical algorithms at NVIDIA, advancing solver performance for scientific, engineering, and industrial simulations. Apply Python and GPU computing to AI-native research.

This senior applied research scientist role focuses on ML methods inside and around numerical solvers. You will develop AI-guided multigrid, solver-in-the-loop learning, differentiable simulation, and hybrid numerical or ML methods. The work spans NVIDIA platforms, NVIDIA Research, universities, and industrial simulation teams.

Key Responsibilities:

- Research AI-assisted numerical methods for large-scale simulations
- Invent learned preconditioners and AI-guided multigrid methods
- Build solver-in-the-loop pipelines using simulation data
- Measure convergence, robustness,



correctness, and end-to-end speedup
- Collaborate across NVIDIA numerical and simulation platforms

Requirements:

- PhD or equivalent experience in a related field
- Five years of relevant work or research experience
- Machine learning and scientific computing background
- Experience with PyTorch, JAX, Python, and GPU computing
- Knowledge of PDEs, sparse linear algebra, and iterative solvers

Apply scientific machine learning, numerical algorithms, and GPU computing to NVIDIA’s AI-native solver research.

📌 Senior AI Numerical Methods Scientist (Canada)
🏢 NVIDIA
📍 Canada